Flattening the curve

We quantify attening the curve under the assumption of a soft quarantine in the spread of a contagious viral disease in a society. In particular, the maximum daily infection rate is expected to drop by twice the percentage drop in the virus reproduction number. The same percentage drop is expected for the maximum daily hospitalization or fatality rate. A formula for the expected maximum daily fatality rate is given. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Optimization Design of X-ray Flattening Filter and Shielding of 25 MeV Electron Accelerator Used for Blood Irradiator

According to the epidemic prevention requirements of the coronavirus disease 2019 and technical requirements of blood irradiators, a new type of blood irradiator based on X band 2.5 MeV electron linear accelerator has been developed at Xihua University. In this paper, MCNP5 was used to optimize the design of flattening filter and shielding of X ray beam of the blood irradiator, and relevant experimental verification was carried out. After optimization design, the X ray beam flatness of the blood irradiator is improved from 59.8% to 92.4%, the weight of the shielding structure is reduced, and the maximum dose rate at 50 mm around the shielding body is 1 μSv/h, which is much better than the Chinese national standard of blood irradiator. © 2022, Editorial Board of Nuclear Electronics & Detection Tech. All right reserved.

COVID Recovery of FMCG Industries - India vs Globe

All the countries of the world are facing humanity's biggest crisis since World War II. Almost every country has been affected by the devastating Coronavirus disease (COVID-19). An outbreak from China has gone everywhere. In the last almost year, Corona's epicenter has been shifted from China to Europe to the United States. By this time, over 1.5 million people had been affected by COVID-19 and about 80,000 people had died worldwide. Indirectly, billions of people have been suffering from the impact of the global pandemic of COVID-19. What is disturbing is that the numbers likely stem from under-reporting, and may probably rise alarmingly in the weeks ahead if we factor in asymptomatic patients and rapid tests. Given that the pandemic-driven crisis is constantly changing, countries are desperate to flattening the curve for COVID-19. Surely, this Coronavirus has put the world economy at a major risk Coronavirus ravages the economic foundations of world trade. Commentators have identified this outbreak as an outcome of hyper-globalization or starting of de-globalization. However, the world is going to face recession;and the global losses, according to some commentators, may exceed World Wars I and II combined. At the same time, the falling world price of crude oil has added further anxieties. Several estimates are now available on the economic loss and post-COVID-19 growth path, and most of the estimates show that the world is already in an economic crisis. South and Southeast Asian countries are no exception. They are heavily affected, health or otherwise. Countries are under full or partial lockdown for the last few weeks. It is a global challenge and a global response is called for. Flattening the COVID-19 curve together helps everyone in an inclusive manner. Unlike the 2007-08 Global Financial Crisis, it is primarily a health crisis, which has given birth to an economic shock. Meanwhile, the world order has been changing fast. Several theories are being postulated. Anti-globalization rhetoric venom is now unfurled. In such unfolding "New Normal" of the world order, the consensus is that countries need to save the earth from the epidemic if we need to live together.

A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating R0 and social distancing behaviour.

We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R0 for each CSA. Values of R0 ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index cflatten. Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found cflatten to be more influential in the clustering process than R0. Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R0 itself.

Dynamic Model to Predict the Flattening of the Covid-19 Outbreak Curve in India

This paper aims to forecast and visualize the confirmed cases, deaths, and recoveries of COVID-19 in India and also predict the end of the growth of COVID-19 cases in India. The methods used for the prediction of future COVID19 cases are machine learning techniques, improved logistic growth equation with a dynamic rate of infection, and automation of the calculations using Python programming language. The paper discusses the current models being used to predict the flattening of the curve, and the pros and cons of using these techniques. The paper then presents the solution and results achieved using our method. The average accuracy percentage of predictions of total confirmed cases was 85.6%, deaths were 84.5%, and recoveries were 83.8%. According to the predictions, the curve started to flatten in October and the curve will completely flatten in the 2nd week of January which confirms the situation that prevailed in India. © 2022 IEEE.

Five common misconceptions regarding flattening-the-curve of COVID-19.

In the fight against COVID-19 pandemic, the phrase "Flattening the curve" (FTC) has become a rallying cry, popularized by government leaders and journalist in the news and on the social media. FTC is a succinct way of communicating an important public health message that physical distancing, mask-wearing and other public health measures will decrease the peak number of cases and prevent the healthcare system from being overwhelmed. However, while the message of FTC is right in the sense that limiting transmission will reduce the peak number of cases, some visualizations used to illustrate its effect are incorrect from an infectious disease modelling point of view. The misconceptions are misinterpretations of flattened curves, the effect of FTC on the duration of the pandemic, the dynamics of the curve to be flattened, and the overestimation of the importance of FTC.

Flattening the curve

We quantify attening the curve under the assumption of a soft quarantine in the spread of a contagious viral disease in a society. In particular, the maximum daily infection rate is expected to drop by twice the percentage drop in the virus reproduction number. The same percentage drop is expected for the maximum daily hospitalization or fatality rate. A formula for the expected maximum daily fatality rate is given. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Public healthcare system capacity during COVID-19: A computational case study of SARS-CoV-2.

AIM: Coronavirus Disease (COVID-19) is spreading typically to the human population all over the world and the report suggests that scientists have been trying to map the pattern of the early transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) since it has been reported as an epidemic. Our main aim is to show if the rise-in-cases proceeds in a gradual and staggered manner instead of soaring quickly then we can suppress the burden of the health system. In this new case study, we are attempting to show how to control the outbreak of the infectious disease COVID-19 via mathematical modeling. We have examined that the method of flattening the curve of the coronavirus, which increases the recovery rate of the infected individuals and also helps to decrease the number of deaths. In this pandemic situation, the countries like Russia, India, the United States of America (USA), South Africa, and the United Kingdom (UK) are leading in front where the virus is spreading in an unprecedented way. From our point of view, we establish that if these countries are following the method of flattening the curve like China and South Korea then these countries can also overcome this pandemic situation. METHOD: We propose a Susceptible, Infected, and Recovered (SIR) mathematical model of infectious disease with onset data of COVID-19 in Wuhan and international cases, which has been propagated in Wuhan City to calculate the transmission rate of the infectious virus COVID-19 until now. To understand the whole dynamics of the transmission rate of coronavirus, we portray time series diagrams such as growth rate diagram, flattening the pandemic curve diagram, infected and recovered rate diagram, prediction of the transmission of the disease from the available dataset in Wuhan, and internationally exported cases from Wuhan. RESULTS: We have observed that the basic reproduction number in Wuhan declined from 2.2 (95% Confidence Interval [CI] 1.15-4.77) to 1.05 (0.41-2.39) and the mean incubation period was 5.2 days (95% [CI], 4.1-7.0). Interestingly the mean value lies between 2 and 2.5 for COVID-19. The doubling time of COVID-19 was registered 7.4 days (95% CI, 5.3-19) in the early stages and now the value decreases to -4.9 days. Similarly, we have observed the doubling time of the epidemic in South Korea decreased to -9.6 days. Currently, the doubling time of the epidemic in Russia, India, and the USA are 19.4 days, 16.4 days, and 41 days, respectively. We have investigated the growth rate of COVID-19 and plotted the curve flattening diagram against time. CONCLUSION: Via flattening the curve method, China and South Korea control the transmission of the fatal disease COVID-19 in the human population. Our results show that these two countries initially sustained pandemics in a large portion of the human population in the form of virus outbreaks that basically prevented the virus from spreading further and created ways to prevent community transmission. The majority portion of the people are perfectly fine, who are quarantined strictly and never get sick, but the portion of people who have developed symptoms is quickly isolated further.

A versatile web app for identifying the drivers of COVID-19 epidemics.

BACKGROUND: No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. METHODS: Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. RESULTS: We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world's fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. CONCLUSION: Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.

Comment on "Poorly known aspects of flattening the curve of COVID-19″.

This short research note describes and summarizes several recent peer-reviewed and non-peer-reviewed studies on the concept of flattening-the-curve (FTC) in the context of the COVID-19 pandemic. This note also highlights contradictory findings of these studies in terms of the effect of FTC on the total number of infections (the final epidemic size), and poses a research problem for future studies.

Understanding the emerging and reemerging terminologies amid the COVID-19 pandemic.

Coronavirus disease (COVID-19) has been declared as a Public Health Emergency of International Concern by the World Health Organization (WHO). During this phase of the health crisis posed by the COVID-19 pandemic, news in print, electronic as well as the social media is abuzz with several emerging and reemerging terminologies. Some of them, such as "social distancing," "infodemic," "flattening the curve," "quarantine," "cluster containment," and others were not in routine use but have suddenly reemerged and become the key toward understanding the disease and its prevention. Many of these terms have been a part of public health strategies used for centuries for containment of the spread of infectious diseases. These terms span across social, epidemiological, and administrative contexts concerning the COVID-19 pandemic. Our article aims to present a better understanding of the meaning and origin of these terms and their application in the context of the current pandemic based on a review of the available literature such as chapters from textbooks, published guidelines of the WHO and Centre for Disease Control and Prevention (CDC) and published articles in journals and newspapers through a comprehensive search of the electronic database in English.

Poorly known aspects of flattening the curve of COVID-19.

A negative correlation between the final ceiling of the logistic curve and its slope, established long time ago via a simulation study, motivated this closer look at flattening the curve of COVID-19. The diffusion of the virus is analyzed with S-shaped logistic-curve fits on the 25 countries most affected in which the curve was more than 95% completed at the time of the writing (mid-May 2020.) A negative correlation observed between the final number of infections and the slope of the logistic curve corroborates the result obtained long time ago via an extensive simulation study. There is both theoretical arguments and experimental evidence for the existence of such correlations. The flattening of the curve results in a retardation of the curve's midpoint, which entails an increase in the final number of infections. It is possible that more lives are lost at the end by this process. Our analysis also permits evaluation of the various governments' interventions in terms of rapidity of response, efficiency of the actions taken (the amount of flattening achieved), and the number of days by which the curve was delayed. Not surprisingly, early decisive response-such as countrywide lockdown-proves to be the optimum strategy among the countries studied.

Population density index and its use for distribution of Covid-19: A case study using Turkish data.

Since March 2020, many countries around the world have been experiencing a large outbreak of a novel coronavirus (2019-nCoV). Because there is a higher rate of contact between humans in cities with higher population weighted densities, Covid-19 spreads faster in these areas. In this study, we examined the relationship between population weighted density and the spread of Covid-19. Using data from Turkey, we calculated the elasticity of Covid-19 spread with respect to population weighted density to be 0.67 after controlling for other factors. In addition to the density, the proportion of people over 65, the per capita GDP, and the number of total health care workers in each city positively contributed to the case numbers, while education level and temperature had a negative effect. We suggested a policy measure on how to transfer health care workers from different areas to the areas with a possibility of wide spread.